Main
Timothy Keyes
I am a data scientist, bioinformatician, and cancer biologist. In my work, I develop statistical and machine learning algorithms for analyzing high-dimensional single-cell data and predicting clinical outcomes in cancer patients.
I am currently searching for a position at the intersection of biomedical data science, machine learning, and medicine where I can use data to solve problems relevant to human health.
Education
M.D./Ph.D. - Cancer Biology
Stanford University
Stanford, CA
Current - 2015
M.S. - Biomedical Informatics (concurrent with MD/PhD)
Stanford University
Stanford, CA
Current - 2020
B.A. - Psychology and Computational Neuroscience
Princeton University
Princeton, NJ
2014 - 2010
- Summa cum laude
- GPA: 3.99
Employment
Data Science Mentor - Posit Academy
Posit, PBC (formerly RStudio, PBC)
Stanford, CA
Current - 2022
Graduate Intern - Oncology Bioinformatics, gRED
Genentech, Inc
South San Francisco, CA
2022
Select Publications
{tidytof}: A user-friendly framework for scalable and reproducible high-dimensional cytometry data analysis.
Under review (copy available upon request)
N/A
2022
- Keyes TJ, Koladiya A, Lo YC, Nolan GP, Davis KL.
- Project website: https://keyes-timothy.github.io/tidytof/
CytofIn enables Integrated Analysis of Public Mass Cytometry Datasets using Generalized Anchors
N/A
2022
- Lo YC, Keyes TJ, Jager A, Sarno J, Domizi P, Majeti R, Sakamoto KM, Lacayo N, Mulligan CG, Waters J, Sahaf B, Bendall SC, Davis KL
A cancer biologist's primer on machine learning applications in high-dimensional cytometry
N/A
2020
- Keyes TJ, Domizi P, Lo YC, Nolan GP, and Davis KL